Lung cancer is responsible for the greatest number of cancer related deaths in the United States. The primary precursor to lung cancer is the development of pulmonary nodules. Several diagnostic procedures are available to detect these nodules including pulmonary function tests, blood tests, biopsy, and imaging tests such as X-ray, magnetic resonance imaging (MRI), computed tomography (CT), and positron emission tomography (PET). Regardless of the diagnostic procedure used, the ultimate diagnosis is usually confirmed by completing a biopsy.
The advent of low-dose helical computed tomography has made it possible to provide relatively low risk screening for high risk patients. Though still somewhat controversial, results of the National Lung Screening Trial (NLST) have shown a 20% decrease in mortality with the use of low-dose CT compared to X-ray findings. The sensitivity of the procedure is its bane; many of the detected nodules are not cancerous.
Accurate classification (or prediction) of pulmonary nodules to be cancerous is key to determining further diagnosis and treatment options. In order to provide medical personnel with the information to accurately determine the nature of the nodule, several computer aided diagnosis systems have been created to classify pulmonary nodules. Traditionally, these systems have been based on size and volume measurements.